基于合群度-隶属度噪声检测及动态特征选择的改进AdaBoost算法
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王友卫,凤丽洲
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Improved AdaBoost algorithm using group degree and membership degree based noise detection and dynamic feature selection
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You-wei WANG,Li-zhou FENG
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表 3 不同噪声检测算法耗时比较 |
Tab.3 Comparison of consuming timeofdifferent noise detection algorithms |
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s | 数据集 | ts | 文献[8] | 文献[9] | 文献[10] | 文献[11] | 本研究 | Spambase | 2.215 | 2.852 | 2.882 | 67.287 | 2.583 | AD | 0.646 | 0.935 | 1.051 | 252.627 | 0.917 | KDD99 | 0.342 | 0.472 | 0.542 | 21.612 | 0.433 | DrivFace | 0.086 | 0.102 | 0.112 | 367.372 | 0.089 | Arrhythmia | 0.035 | 0.043 | 0.052 | 18.223 | 0.038 | AntiVirus | 0.021 | 0.034 | 0.039 | 18.658 | 0.031 | Dermatology | 0.023 | 0.041 | 0.036 | 5.329 | 0.033 | Amazon | 0.036 | 0.089 | 0.083 | 88.173 | 0.077 |
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